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How Embedded Analytics Can Boost Customer Engagement in 2024

July 2, 2024

You May Be Here Because:

  • You’re looking for ways to use data to better engage and retain your users.
  • You want to enhance your end user experience and engagement.
  • You’re interested in integrating embedded analytics to your SaaS platform.
  • You need examples of how embedded analytics can be effectively implemented.

Embedded analytics isn’t just about throwing charts into your app. It's about creating a seamless, intuitive experience that keeps users coming back. Think of embedded analytics as the secret sauce that turns your app into a must-have tool for your users. When data insights are readily available and actionable, users are more likely to engage deeply with your platform. Let's explore how embedded analytics can significantly boost customer engagement for your SaaS with some insightful update.

Benefits of Embedded Analytics for Customer Engagement

End User Experience

Embedded analytics ensures a smoother, more engaging user experience by providing the data users need precisely when and where they need it. This integration makes data a natural part of the user workflow, increasing efficiency and satisfaction. Some key points include:

  • Users can easily share data without needing advanced data literacy, making the process straightforward for everyone.
  • Integrated Workflow: Unlike traditional BI tools, embedded analytics allow users to access necessary data without switching tools, streamlining their processes and saving time.
  • In-app analytics is more value as it shows you care about providing value to end-users - transparency = trust.
  • Provides reasons for users to log back into your app, enhancing engagement and retention by offering continuous value.

Personalized Insights with Custom Reporting

Personalization makes analytics more relevant and engaging by tailoring dashboards and reports to each user's needs and preferences. This means allowing users to customize their experience by selecting the metrics they want to prioritize, choosing their preferred units of measurement, and deciding whether to view data in graphical or tabular formats. Personalization helps tailor the analytics to each user's role and preferences, enhancing their interaction with your platform and making the data more actionable. For instance:

  • Role-Specific Dashboards: Customize dashboards for different roles (e.g., sales, marketing, operations) to display the most relevant metrics for each.
  • User Preferences: Allow users to set their preferences for data visualization types, metrics displayed, and notification settings.
  • Behavioral Adaptation: Adjust analytics based on user behavior patterns, showing more of what they frequently access and less of what they don't.

Perfect balance of no-code and pro-code

Vizzly aims to find the perfect balance between no-code and pro-code. For example, non-technical stakeholders can build datasets and dashboards with a no-code editor - however, developers can customize and extend the dashboard embed with code to align look, feel and behaviour of the dashboard with the rese of their application.

For example, Vizzly offers a powerful Theme API for overriding CSS objects and the ability to rip out and inject custom components, such as loading icons or date pickers, should you have your own component library or design system. With Vizzly, developers can also create, manage, and delete dashboards and views programmatically with the JS Services Package. There’s really no limit to what developers can create with Vizzly, and that’s the idea here—we help B2B SaaS orgs build best-in-class analytics experiences without compromise.

Increased Retention Rates

When users consistently see value through direct data insights within your app, they are more likely to stay engaged and renew their subscriptions. Demonstrating ongoing value keeps them coming back. Providing users with continuous insights and showing tangible benefits of using your app helps build loyalty and reduces churn. Embedded analytics helps maintain user interest and engagement by delivering timely, relevant data that supports their goals and objectives.

What you need to look for when Embedded Analytics in Your SaaS Platform

1. Look for time-to-vale, not time-to-market: Prioritize solutions that deliver immediate, meaningful insights rather than just quick deployment. Ensure your analytics provide real value from day one.

2. Control through extensibility: No-code isn’t enough. Often code is needed to have longevity with any third-party integration which means having a solution extensible with code is critical even if the initial ‘dashboard MVP’ doesn’t need to be overly customised.

3. Performance: Fast data loading is crucial, especially for real-time use cases. Data must load quickly to keep customers satisfied. Optimize your data infrastructure to support real-time analytics and provide sub-second query responses.

4. Optionality for end-user configuration: Options for letting end-users configure the dashboard or reporting layer with custom reporting or self-serve analytics satisfy different data requirements, enhance engagement, and improve retention.

5. Design system alignment: Aesthetics are important—it's not enough to simply customize the color of the charts and font of the text. You need complete control over CSS properties and more to achieve full alignment with your design system.

6. Empower non-tech stakeholdes to iterate and maintain: Provide easy-to-use, no-code editors for dashboards and datasets, allowing non-technical users to update and manage content on their own, fostering continuous adaptation without needing specialized technical skills.


Embedded analytics can transform how users interact with your SaaS platform which in-turn drives better engagement and retention. By integrating analytics seamlessly into your application, you provide users with the tools they need to make informed decisions, increasing the value and stickiness of your product.

See how Vizzly compares to open source chart libraries for embedding analytics in your SaaS app.

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